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This chapter introduces electroencephalography (EEG), a measure of neurophysiological activity, as a critical method for investigating individual and team decision-making and cognition. EEG is a useful tool for expanding the theoretical and research horizons in organizational cognitive neuroscience, with a lower financial cost and higher portability than other neuroimaging methods (e.g., functional magnetic resonance imaging). This chapter briefly reviews past work that has applied cognitive neuroscience methods to investigate cognitive processes and outcomes. The focus is on describing contemporary EEG measures that reflect individual cognition and compare them to complementary measures in the field of psychology and management. The authors discuss how neurobiological measures of cognition relate to and may predict both individual cognitive performance and team cognitive performance (decision-making). This chapter aims to assist scholars in the field of managerial and organizational cognition in understanding the complementarity between psychological and neurophysiological methods, and how they may be combined to develop new hypotheses in the intersection of these research fields.

Introduction: The Covid-19 pandemic wreaked havoc on the organisations in the form of increased job demands which manifested through increased workload, time pressure, etc. Similarly, stress and burnout engulfed the employees. Remote work became the new normal post-pandemic. Remote workers require more engagement. This has brought Artificial Intelligence (AI) to the forefront for engaging employees in the new normal.

Purpose: With limited studies on AI-enabled employee engagement in the new normal, this study investigates and proposes a conceptual framework of employee engagement in the context of AI and its impact on organisations.

Methodology: A systematic review and meta-synthesis method is undertaken. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes.

Findings: Since many organisations are turning to remote work post-pandemic and remote work requires more engagement, organisations are investing in AI to boost employee engagement in the new normal. Several antecedents of employee engagement such as quality of work life, diversity and inclusion, and communication are facilitated by AI. AI helps enhance the quality of work life by playing a major role in providing fair compensation, safe and healthy working conditions, immediate opportunity to use and develop human capacities, continued growth and security, work and total life space, and social relevance of work life. This has led to positive organisational outcomes like increased productivity, employee well-being, and decreased attrition rate. Furthermore, AI helps in measuring employee engagement. The various tools of AI, such as wearable technology, digital biomarker, neural network, data mining, data analytics, machine learning (ML), natural language processing (NLP), etc., have gone a long way in engaging employees in the new normal.

Multiple sclerosis (MS) is a chronic condition with variable physical, cognitive, and quality of life impacts. Little research has investigated how MS outcomes vary by social identity (race, gender, disability, age, sexual orientation, and nationality) and social location (place within systems of power and privilege). However, emerging evidence points to racial and ethnic group disparities in MS outcomes. This chapter integrates core concepts from the life course perspective and an intersectional feminist disability framework to interrogate the role of diagnosis pathways in determining differential MS outcomes. MS diagnosis pathways (the time from symptom onset to the point of diagnosis) are a logical place to begin this work given the varying nature of symptom onset and the importance of a quick diagnosis for optimal MS outcomes. Whereas the life course perspective provides a framework for understanding disability transitions and pathways across the life span, an intersectional feminist disability framework centers disability within an axis of overlapping social identities and locations. The combination of both frameworks provides an approach capable of examining how MS disparities and inequities emerge in different contexts over time. The chapter begins with an overview of MS and current knowledge on disparities (mainly racial) in MS prevalence, diagnosis, and outcomes. The chapter proceeds to describe the utility of key concepts of both the life course perspective and intersectional frameworks when researching health disparities. Finally, the chapter ends with a theoretical application of an intersectional feminist disability life course perspective to investigate disparities in MS diagnosis pathways.